Legal claims defining the scope of protection. Each claim is shown in both the original legal language and a plain English translation.
1. A device for determining vehicle operator gestures and providing the vehicle operator gestures to at least one individual other than the vehicle operator, the device comprising: a previously classified image data receiving module stored on a memory that, when executed by a processor, causes the processor to receive previously classified image data from at least one previously classified image database, wherein the previously classified image data is representative of previously classified vehicle operator gestures; a current image data receiving module stored on a memory that, when executed by a processor, causes the processor to receive current image data from at least one vehicle interior sensor, wherein the current image data is representative of current vehicle operator gestures, wherein the current image data is representative of rotated and scaled postures that are normalized for a range of different vehicle operators, and wherein the current image data includes images and/or extracted image features that are representative of a vehicle occupant interacting with an electronic device, a vehicle occupant interacting with an onboard computer interface, a vehicle occupant using a cellular telephone, a vehicle occupant looking out a vehicle side window, a vehicle occupant adjusting a vehicle radio, a vehicle occupant adjusting a vehicle heating, ventilation and air conditioning system, two vehicle occupants talking with one-another, a vehicle occupant reading a book or magazine, a vehicle occupant putting on makeup, a vehicle occupant looking at themselves in a mirror, a vehicle occupant eating, or a vehicle occupant drinking; a current image data classification module stored on a memory that, when executed by a processor, causes the processor to classify the current image data by comparing the current image data to the previously classified image data, wherein the currently classified image data is representative of at least one current vehicle operator gesture; and a currently classified image data transmission module stored on a memory that, when executed by a processor, causes the processor to transmit the currently classified image data to at least one other vehicle.
Automotive safety and driver assistance. This invention addresses the need to understand and communicate driver actions and attention levels within a vehicle. The system comprises several functional modules. A previously classified image data receiving module accesses a database containing pre-labeled images of various driver gestures. This allows the system to learn from a known set of actions. A current image data receiving module captures real-time images from sensors within the vehicle. These images represent the driver's current gestures and are processed to account for variations in driver size and orientation, ensuring consistent recognition. The captured data can include raw images or extracted features, specifically designed to identify interactions with electronic devices, onboard interfaces, telephones, looking out windows, adjusting vehicle controls like radios or HVAC, conversations between occupants, reading, applying makeup, checking mirrors, eating, or drinking. A current image data classification module compares the incoming real-time image data against the previously classified gesture data to identify and categorize the driver's current actions. Finally, a currently classified image data transmission module sends the identified gesture information to other vehicles, enabling inter-vehicle communication of driver status or intentions.
2. The device as in claim 1 , wherein the at least one vehicle interior sensor is selected from: at least one digital image sensor, at least one ultra-sonic sensor, at least one radar-sensor, at least one infrared light sensor, or at least one laser light sensor.
This invention relates to a vehicle interior monitoring system designed to enhance passenger safety and comfort by detecting and analyzing occupant conditions. The system includes at least one sensor installed within the vehicle interior to monitor various parameters, such as passenger presence, posture, or activity. The sensor types may include digital image sensors, ultrasonic sensors, radar sensors, infrared light sensors, or laser light sensors. These sensors collect data on the vehicle's occupants, which is then processed to assess factors like seat occupancy, passenger movement, or potential distress. The system may also integrate with other vehicle systems to trigger safety measures, such as seatbelt adjustments or collision avoidance, based on the sensor data. The goal is to improve occupant safety by providing real-time monitoring and automated responses to detected conditions. The use of multiple sensor types allows for comprehensive and reliable detection, ensuring accurate and timely interventions. This technology addresses the need for advanced occupant monitoring in vehicles to prevent accidents and enhance passenger well-being.
3. The device as in claim 1 , wherein at least one vehicle operator gesture is determined using a probability function, and wherein a probability of a crash occurring is determined by analyzing at least one of: a current state of one or more drivers, dynamics of one or more vehicles, trajectories of one or more vehicles, locations of one or more road side equipment, locations of one or more infrastructure fixtures, locations of one or more road users, trajectories of one or more road users, trajectories of one or more pedestrians, or locations of one or more pedestrians.
The invention relates to a vehicle safety system that assesses crash risk by analyzing driver gestures and environmental factors. The system determines the likelihood of a crash by evaluating various inputs, including driver behavior, vehicle dynamics, and surrounding conditions. Driver gestures are analyzed using a probability function to predict potential risks. The system also assesses crash probability by examining multiple factors, such as the current state of drivers, vehicle trajectories, roadside equipment locations, infrastructure fixtures, road user positions, and pedestrian movements. By integrating these data points, the system provides a comprehensive risk assessment to enhance vehicle safety. The primary goal is to proactively identify and mitigate crash risks by continuously monitoring and analyzing real-time data from both the vehicle and its environment. This approach helps improve collision avoidance and overall road safety.
4. The device as in claim 1 , wherein the current image data is representative of a three-dimensional representation of at least one occupant within the vehicle interior.
This invention relates to vehicle occupant monitoring systems that use image data to analyze and track occupants within a vehicle interior. The technology addresses the challenge of accurately detecting and interpreting occupant positions, movements, and behaviors in real-time to enhance safety and functionality. The system captures current image data of the vehicle interior, which is processed to generate a three-dimensional representation of at least one occupant. This 3D representation allows for precise tracking of the occupant's posture, gestures, and spatial positioning, enabling applications such as driver monitoring, child seat detection, or occupant status assessment. The system may integrate with other vehicle systems to trigger alerts, adjust settings, or activate safety measures based on the analyzed data. By providing detailed spatial and contextual information, the invention improves upon traditional two-dimensional imaging methods, offering more accurate and reliable occupant monitoring for advanced driver assistance and autonomous vehicle applications. The 3D representation can be used to detect critical conditions, such as driver drowsiness, improper seating, or unauthorized occupants, ensuring a safer and more responsive vehicle environment.
5. The device as in claim 1 , wherein the previously classified image data is representative of a three-dimensional representation of at least one occupant within the vehicle interior.
This invention relates to vehicle occupant monitoring systems that use image data to classify and analyze occupants within a vehicle interior. The system captures images of the vehicle interior and processes these images to generate a three-dimensional representation of at least one occupant. This representation is then used to classify the occupant, such as determining their position, posture, or identity. The system may also track changes in the occupant's state over time, such as detecting drowsiness or distraction. The three-dimensional representation improves accuracy by providing depth information, allowing the system to distinguish between overlapping occupants or objects. The system may integrate with vehicle safety features, such as adjusting seatbelt tension or triggering alerts based on the occupant's classification. The invention enhances occupant monitoring by providing detailed spatial data, improving safety and personalization in vehicle environments.
6. The device as in claim 1 , wherein the previously classified image data includes images and/or extracted image features that have previously been classified as being representative of a vehicle occupant interacting with an electronic device, a vehicle occupant interacting with an onboard computer interface, a vehicle occupant using a mobile device, a vehicle occupant looking out a vehicle side window, a vehicle occupant adjusting a vehicle radio, a vehicle occupant adjusting a vehicle heating, ventilation and air conditioning system, two vehicle occupants talking with one-another, a vehicle occupant reading a book or magazine, a vehicle occupant putting on makeup, a vehicle occupant looking at themselves in a mirror, a vehicle occupant eating, or a vehicle occupant drinking.
This invention relates to a device for analyzing vehicle occupant behavior using previously classified image data. The device processes images or extracted image features to detect and classify specific occupant activities within a vehicle. The classified data includes interactions with electronic devices, onboard computer interfaces, or mobile devices, as well as behaviors like looking out a side window, adjusting vehicle controls (radio, HVAC), reading, applying makeup, using a mirror, eating, or drinking. Additionally, the device can identify social interactions, such as two occupants conversing. The system leverages pre-labeled image data to recognize these activities, enabling applications in driver monitoring, safety systems, or in-vehicle experience optimization. The invention improves upon existing occupant monitoring by expanding the range of detectable behaviors, providing more comprehensive insights into occupant activities and potential distractions. This enhances safety and personalization features in vehicles by accurately identifying and responding to various occupant states.
7. A computer-implemented method for determining vehicle operator gestures and for transmitting the vehicle operator gestures to at least one individual other than the vehicle operator, the method comprising: receiving, at a processor of a computing device, previously classified image data from at least one previously classified image database in response to the processor executing a previously classified image data receiving module, wherein the previously classified image data is representative of previously classified vehicle operator gestures; receiving, at a processor of a computing device, current image data from at least one vehicle interior sensor a current image data receiving module, in response to the processor executing a current image data receiving module, wherein the current image data is representative of at least one current vehicle operator gesture, wherein the current image data is representative of rotated and scaled postures that are normalized for a range of different vehicle operators, and wherein the current image data includes images and/or extracted image features that are representative of a vehicle occupant interacting with an onboard computer interface, a vehicle occupant interacting with an electronic device, a vehicle occupant interacting with an onboard computer interface, vehicle occupant locations/orientations, cellular telephone locations/orientations, vehicle occupant eye locations/orientations, vehicle occupant head location/orientation, vehicle occupant hand location/orientation, a vehicle occupant torso location/orientation, a seat belt location, or a vehicle seat location/orientation; classifying, using a processor of a computing device, at least one gesture associated with a vehicle operator, based on a comparison of the current image data with the previously classified image data, in response to the processor executing a current image data classification module; and transmitting, using a processor of a computing device, the currently classified image data to at least one other vehicle, in response to the processor executing a currently classified image data transmission module.
This invention relates to a computer-implemented method for detecting and transmitting vehicle operator gestures to other individuals. The system addresses the challenge of accurately identifying and communicating driver gestures in real-time, which is crucial for applications like vehicle-to-vehicle communication, driver monitoring, or assisted driving systems. The method involves receiving previously classified image data from a database, where the data represents known vehicle operator gestures. Concurrently, current image data is captured from vehicle interior sensors, such as cameras or other imaging devices. This data includes images or extracted features representing various interactions, including gestures, hand positions, head orientations, and interactions with onboard systems or personal devices. The system normalizes the data to account for variations in posture, rotation, and scale across different drivers. A processor then classifies the current gestures by comparing the incoming sensor data with the pre-classified database. Once classified, the gesture data is transmitted to at least one other vehicle or external recipient. This enables real-time sharing of driver behavior, which can be used for safety alerts, coordination between vehicles, or remote monitoring. The system ensures accurate gesture recognition despite variations in driver posture and environmental conditions.
8. The method as in claim 7 , wherein the at least one vehicle interior sensor is selected from: at least one digital image sensor, at least one ultra-sonic sensor, at least one radar-sensor, at least one infrared light sensor, or at least one laser light sensor.
This invention relates to vehicle interior monitoring systems designed to enhance occupant safety and comfort. The system uses at least one sensor to detect the presence, position, or movement of occupants within a vehicle. The sensor data is processed to determine if an occupant is in a vulnerable state, such as being unrestrained or improperly seated, and triggers appropriate responses like alerts or safety measures. The system may also adjust vehicle settings, such as climate control or seat positioning, based on occupant detection. The invention ensures real-time monitoring and adaptive responses to improve passenger safety and comfort. The sensors used include digital image sensors, ultrasonic sensors, radar sensors, infrared light sensors, or laser light sensors, each capable of detecting occupants and their conditions accurately. The system integrates these sensors to provide comprehensive monitoring and timely interventions, addressing the need for proactive safety measures in modern vehicles.
9. The method as in claim 7 , wherein the current image data is representative of either a two-dimensional or a three-dimensional representation of at least one occupant within the vehicle interior.
This invention relates to vehicle occupant monitoring systems that analyze image data to determine occupant presence, position, or state. The system captures current image data of the vehicle interior, which may represent occupants in either two-dimensional or three-dimensional form. The image data is processed to detect and analyze occupant characteristics, such as position, posture, or activity, using computer vision techniques. The system may compare the current image data with reference data to identify changes in occupant state, such as movement, distraction, or potential safety risks. The analysis may involve depth sensing, object recognition, or motion tracking to enhance accuracy. The system can generate alerts or adjust vehicle settings based on the analysis, improving occupant safety and comfort. The method ensures compatibility with various imaging technologies, including 2D cameras and 3D sensors, allowing flexible deployment in different vehicle models. The invention addresses the need for reliable occupant monitoring to prevent accidents, enhance driver assistance, and enable personalized vehicle responses.
10. The method as in claim 7 , wherein at least one vehicle operator gesture is determined using a probability function, and wherein a probability of a crash occurring is determined by analyzing at least one of: a current state of one or more drivers, dynamics of one or more vehicles, trajectories of one or more vehicles, locations of one or more road side equipment, locations of one or more infrastructure fixtures, locations of one or more road users, trajectories of one or more road users, trajectories of one or more pedestrians, or locations of one or more pedestrians.
This invention relates to vehicle safety systems that analyze driver behavior and environmental factors to predict and prevent collisions. The system determines the likelihood of a crash by evaluating various inputs, including driver gestures, vehicle dynamics, and the positions and movements of other road users, infrastructure, and pedestrians. Driver gestures are assessed using a probability function to gauge the operator's actions and intentions. The system also analyzes real-time data such as vehicle trajectories, roadside equipment locations, and pedestrian movements to calculate crash probabilities. By integrating these factors, the system provides a comprehensive risk assessment to enhance safety. The method ensures that multiple variables are considered, allowing for accurate and timely collision predictions. This approach helps mitigate accidents by identifying high-risk scenarios before they occur, enabling proactive safety measures. The system is designed to operate in dynamic environments, adapting to changing conditions to maintain accurate risk assessments. The invention improves upon existing safety systems by incorporating a broader range of data points and probabilistic analysis, leading to more reliable collision predictions.
11. The method as in claim 7 , wherein the previously classified image data is representative of a three-dimensional representation of at least one occupant within the vehicle interior.
This invention relates to vehicle occupant monitoring systems that use image data to classify and analyze occupants within a vehicle interior. The problem addressed is the need for accurate and detailed occupant detection, particularly in three-dimensional space, to enhance safety features such as airbag deployment, seatbelt adjustments, or driver monitoring. The method involves processing previously classified image data to generate a three-dimensional representation of at least one occupant inside the vehicle. This data is derived from earlier classification steps that identify and categorize occupants based on their position, posture, or other characteristics. The three-dimensional representation allows for precise spatial analysis, enabling the system to determine the occupant's exact location, orientation, and movement within the vehicle. This information can then be used to optimize safety systems, such as adjusting airbag deployment based on the occupant's position or detecting potential distractions for driver monitoring. The method leverages advanced imaging techniques, such as stereo cameras or depth sensors, to capture and process the necessary data. By converting two-dimensional image data into a three-dimensional model, the system improves accuracy in occupant detection and response, addressing limitations of traditional two-dimensional analysis. This approach enhances vehicle safety by providing more reliable and context-aware monitoring of occupants.
12. The method as in claim 7 , wherein the previously classified image data includes images and/or extracted image features that have previously been classified as being representative of known vehicle occupant interacting with an electronic device, vehicle occupant interacting with an onboard computer interface, vehicle occupant locations/orientations, known cellular telephone locations/orientations, known vehicle occupant eye locations/orientations, known vehicle occupant head location/orientation, known vehicle occupant hand location/orientation, a known vehicle occupant torso location/orientation, a known seat belt location, or a known vehicle seat location/orientation.
This invention relates to a method for analyzing vehicle occupant behavior using previously classified image data. The method addresses the challenge of accurately detecting and classifying interactions between vehicle occupants and electronic devices, onboard computer interfaces, and other relevant features within a vehicle. The system leverages pre-existing classified image data, which includes images and extracted image features that have been categorized based on specific vehicle occupant behaviors and positions. These classifications cover a range of scenarios, such as occupants interacting with electronic devices or onboard interfaces, as well as the spatial and orientational data of occupants' eyes, heads, hands, torsos, seat belts, and vehicle seats. The method utilizes this pre-classified data to improve the accuracy and efficiency of real-time occupant monitoring, enabling safer and more responsive vehicle systems. By comparing new image data against the pre-classified dataset, the system can quickly identify and respond to critical occupant behaviors, such as distracted driving or improper seat belt usage. This approach enhances vehicle safety by providing timely feedback and interventions based on well-defined behavioral patterns.
13. A non-transitory computer-readable medium storing computer-readable instructions that, when executed by a processor, cause the processor to determine degrees of vehicle operator risk, the non-transitory computer-readable medium comprising: a previously classified image data receiving module that, when executed by a processor, causes the processor to receive previously classified image data from at least one previously classified image database, wherein the previously classified image data is representative of previously classified vehicle operator risk; a current image data receiving module that, when executed by a processor, causes the processor to receive current image data from at least one vehicle interior sensor, wherein the current image data is representative of current vehicle operator risk, wherein the current image data is representative of rotated and scaled postures that are normalized for a range of different vehicle operators, and wherein the current image data includes images and/or extracted image features that are representative of a vehicle occupant interacting with an electronic device, a vehicle occupant interacting with an onboard computer interface, a vehicle occupant using a cellular telephone, a vehicle occupant looking out a vehicle side window, a vehicle occupant adjusting a vehicle radio, a vehicle occupant adjusting a vehicle heating, ventilation and air conditioning system, two vehicle occupants talking with one-another, a vehicle occupant reading a book or magazine, a vehicle occupant putting on makeup, or a vehicle occupant looking at themselves in a mirror, vehicle occupant locations/orientations, cellular telephone locations/orientations, vehicle occupant eye locations/orientations, vehicle occupant head location/orientation, vehicle occupant hand location/orientation, a vehicle occupant torso location/orientation, a seat belt location, or a vehicle seat location/orientation; a current image data classification module that, when executed by a processor, causes the processor to classify the current image data by comparing the current image data to the previously classified image data, wherein the currently classified image data is representative of at least one current vehicle operator gesture; and a currently classified image data transmission module that, when executed by a processor, causes the processor to transmit the currently classified image data to at least one other vehicle.
This invention relates to a system for assessing vehicle operator risk using image data analysis. The system determines risk levels by comparing real-time images of vehicle occupants with pre-classified image data representing various high-risk behaviors. The system receives current image data from interior vehicle sensors, which captures occupant activities such as using a phone, adjusting vehicle controls, interacting with passengers, or engaging in distracting behaviors like reading or applying makeup. The images are normalized to account for variations in posture, rotation, and scale across different drivers. The system classifies these images by matching them against a database of previously classified risk scenarios, identifying specific gestures or actions that indicate potential risk. The classified data is then transmitted to other vehicles, enabling shared risk assessment. The system aims to enhance road safety by detecting and communicating driver distractions or unsafe behaviors in real time. The technology leverages machine learning to analyze occupant posture, eye gaze, hand movements, and interactions with vehicle systems, providing a comprehensive risk evaluation framework.
14. The non-transitory computer-readable medium as in claim 13 , wherein the vehicle operator degree of risk is determined using a probability function, and wherein a probability of a crash occurring is determined by analyzing at least one of: a current state of one or more drivers, dynamics of one or more vehicles, trajectories of one or more vehicles, locations of one or more road side equipment, locations of one or more infrastructure fixtures, locations of one or more road users, trajectories of one or more road users, trajectories of one or more pedestrians, or locations of one or more pedestrians.
This invention relates to systems for assessing vehicle operator risk in transportation environments. The technology addresses the problem of predicting crash likelihood by analyzing multiple dynamic and static factors to determine a probability-based risk assessment for vehicle operators. The system evaluates a vehicle operator's degree of risk using a probability function that considers various inputs. These inputs include the current state of one or more drivers, vehicle dynamics, vehicle trajectories, locations of roadside equipment, infrastructure fixtures, road users, and pedestrians, as well as the trajectories of road users and pedestrians. By integrating these diverse data points, the system calculates the probability of a crash occurring, enabling proactive risk mitigation. The approach leverages real-time and predictive analytics to enhance safety in transportation networks by identifying high-risk scenarios before they escalate. This method supports automated risk assessment in autonomous or assisted driving systems, infrastructure management, and traffic safety applications. The invention improves upon traditional risk assessment methods by incorporating a broader set of environmental and behavioral factors to provide a more comprehensive and accurate risk evaluation.
15. The non-transitory computer-readable medium as in claim 13 , wherein the current image data is representative of a three-dimensional representation of at least one occupant within the vehicle interior.
This invention relates to vehicle occupant monitoring systems that use image data to analyze and track occupants within a vehicle interior. The system captures image data of the vehicle interior, processes the data to identify and track occupants, and generates a three-dimensional representation of at least one occupant. The three-dimensional representation allows for detailed analysis of occupant position, posture, and movement, which can be used for safety, comfort, and security applications. The system may also compare the current image data with stored data to detect changes in occupant behavior or state, such as drowsiness or distraction. The three-dimensional modeling enhances accuracy in tracking occupant movements and interactions with vehicle features, improving safety systems like airbag deployment or seatbelt adjustments. The system may also integrate with other vehicle systems to provide alerts or automated responses based on occupant conditions. The invention focuses on improving occupant monitoring through advanced image processing and three-dimensional modeling to enhance safety and user experience in vehicles.
16. The non-transitory computer-readable medium as in claim 13 , wherein the previously classified image data includes images and/or extracted image features that have previously been classified as being representative of a vehicle occupant interacting with an electronic device, a vehicle occupant interacting with an onboard computer interface, a vehicle occupant using a cellular telephone, a vehicle occupant looking out a vehicle side window, a vehicle occupant adjusting a vehicle radio, a vehicle occupant adjusting a vehicle heating, ventilation and air conditioning system, two vehicle occupants talking with one-another, a vehicle occupant reading a book or magazine, a vehicle occupant putting on makeup, a vehicle occupant looking at themselves in a mirror, known vehicle occupant locations/orientations, known cellular telephone locations/orientations, known vehicle occupant eye locations/orientations, known vehicle occupant head location/orientation, known vehicle occupant hand location/orientation, a known vehicle occupant torso location/orientation, a known seat belt location, or a known vehicle seat location/orientation.
The invention relates to a computer-implemented system for classifying and analyzing vehicle occupant behavior using image data. The system addresses the challenge of monitoring and understanding occupant activities within a vehicle to enhance safety, comfort, and automation. The technology processes image data from vehicle cameras to detect and classify various occupant interactions, such as using electronic devices, adjusting vehicle controls, or engaging in personal activities like reading or applying makeup. The system leverages previously classified image data to improve recognition accuracy, including identifying specific occupant behaviors like interacting with onboard computers, cellular phones, or vehicle systems (e.g., HVAC or radio). It also tracks spatial and positional data, such as occupant locations, orientations, and the positions of objects like seat belts or mirrors. By analyzing these patterns, the system supports applications like driver distraction detection, automated safety interventions, or personalized in-vehicle experiences. The invention enhances situational awareness within vehicles by combining visual recognition with contextual data to classify and predict occupant actions.
17. The non-transitory computer-readable medium as in claim 13 , wherein the previously classified image data is representative of a three-dimensional representation of at least one occupant within the vehicle interior.
This invention relates to computer vision systems for analyzing vehicle interiors, specifically focusing on classifying and processing image data to detect and represent occupants in three-dimensional space. The system captures images of the vehicle interior using one or more cameras and processes these images to identify and classify occupants, including their positions and postures. The processed data is then used to generate a three-dimensional representation of the occupants, enabling advanced safety and convenience features. The system may also compare the current occupant data with previously classified data to detect changes, such as movements or new occupants, and update the three-dimensional model accordingly. This allows for real-time monitoring of occupant behavior, which can be used for applications like adaptive airbag deployment, personalized climate control, or driver monitoring. The invention improves upon existing systems by providing a more accurate and dynamic representation of occupants, enhancing safety and user experience in vehicles. The three-dimensional modeling capability ensures precise tracking of occupant positions, even in complex seating arrangements or with multiple passengers.
Unknown
September 22, 2020
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